1. Field of the Invention
The methods disclosed herein relate to automated computer data processing, specifically the processing of text into hypertext and associated delivery tools and verification systems therefor.
2. Description of the Related Art
It has been widely recognized that use of clinical guidelines by clinicians is very low, even among those who profess to know about them and agree with them (see, for example, references [1] [2]). (The numbers in square brackets throughout this disclosure refer to the references listed in the “References” section below and are incorporated herein by reference in their entireties.)
Previous studies have documented the inability of traditional means for distributing guidelines, such as publication and didactic educational sessions, to increase their use [3]. This is so primarily for three reasons. First, clinicians may not remember to apply the guideline even if they are aware of it and agree with it. Second, the details of the guideline are not always readily accessible at the site of clinical care. Third, the traditional form of a published guideline may not make it immediately clear how to apply the guideline.
Guidelines traditionally have been distributed in print form in medical journals, books, or monographs. More recently, guidelines have been published electronically either on CD-ROM or in repositories based on the World Wide Web [4]. However, even with electronic distribution, most existing clinical guidelines are text documents. They often contain extensive background and reference material. This additional material is valuable, but once the clinician is familiar with the guideline the background and reference material are not needed for day-to-day clinical practice. It may be difficult to find quickly what is directly useful, e.g., the “bottom line” decision and action steps. This difficulty is due in part to the unstructured nature of text-based guidelines. A simple algorithmic summary of the guideline may not be available and if present, may be located in a variety of locations in the document. In addition, the language in a guideline may be intentionally ambiguous to satisfy the consensus process used to create it, or the guideline may lack coverage, be logically incomplete or appear to be contradictory [5].
Another feature of text-based guidelines that makes them more difficult to apply is that they may specify multiple choices of action and may leave the ultimate choice to the end-user's (e.g., decision maker, physician) judgment without making it clear how the choice is to be made.
Some researchers have promoted the idea of a shareable representation of clinical guidelines. For example, the Guideline Interchange Format (GLIF) [6] encodes explicitly in procedural form the steps for collecting information about a patient and making decisions. This process requires extensive expert encoding in a formal language, and is specifically designed for medical applications. Moreover, while it does produce a machine-interpretable form of the guideline, it does not preserve the relationship of the procedural component to the original published document. This can make it difficult to produce educational or reference applications of the guideline.
What is needed is a better encoding system that, at least in part, automatically encodes or converts text documents into a machine-interpretable or machine-readable form. The type of text documents are preferably not limited to medical documents, but include other types of documents as well. Such a system may also include tools for verifying and validating the encoded documents produced thereby and for adding or editing the system-generated codings. Such a system may also include a specialized coding language tailored to optimize the actual encoding.